Although inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed.We enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests.Our results revealed that binding antibody IgM peaked 14–28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The neutralized fraction subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89)–17.8% (16/90).Two doses of CoronaVac vaccine resulted in limited protection over a short duration. The inactivated vaccine booster can reverse the decrease of antibody levels to prime strain, but it does not elicit potent neutralization against Omicron; therefore, the optimization of booster procedures is vital.Key Research and Development Program of Zhejiang Province; Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission; Major Program of Zhejiang Municipal Natural Science Foundation; Explorer Program of Zhejiang Municipal Natural Science Foundation. The coronavirus disease 2019 (COVID-19), a global health emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has led to unprecedented global healthcare and economic burdens . COVID-1Inactivated COVID-19 vaccines, such as CoronaVac and BBIBP-CorV, were proven to be generally safe and effective in adults in several clinical trials  and are The SARS-CoV-2 variants that have been classified as variants of interest or variants of concern (VOC) by the World Health Organization (WHO) are responsible for multiple waves of infection  and the We explored the dynamic responses and durations of antibodies against SARS-CoV-2 in individuals within 1 year of being vaccinated with an inactivated COVID-19 vaccine and speculated on the protection provided based on the attenuation of neutralizing antibody levels. Furthermore, we evaluated the presence of neutralizing antibodies against Delta and Omicron in volunteers boosted with a third dose of inactivated vaccine.The cross-sectional investigation was conducted in five counties of Zhejiang Province, mainland China , after nationwide COVID-19 vaccinations from May to October 2021. Potential participants aged 18–59 years who had no prior vaccinations or were vaccinated with one or two doses of CoronaVac  were recruited from the community. Individuals with a history of infection with SARS-CoV-2 (based on epidemic surveillance system) or the use of blood products or immunosuppressive drugs were excluded. We randomly enrolled 1067 volunteers, including those on day 0 , day 14±2 (V1-14d), and day 28±3 (V1-28d) after the first vaccine dose, and day 30±3 (V2-1m), day 90±7 (V2-3m), day 180±14 (V2–6 m), day 270±14 (V2-9m), and day 365±30 (V2-12m) after the second dose and collected their venous blood samples (3–5 ml) to detect serum antibody levels . This waIn the prospective cohort study, we recruited 90 healthy adults aged 18–80 years from Jiaxing city, Zhejiang, in June 2021. The main exclusion criteria included previous or later SARS-CoV-2 infection; allergy to any ingredient included in the vaccine; those who had received any blood products or any research medicines or vaccines in the past month; those who had uncontrolled epilepsy or other serious neurological diseases, acute febrile disease, acute onset of chronic diseases, or uncontrolled severe chronic diseases; and those who were unable to comply with the study schedule. Subjects were administered 4 µg/0.5 mL of CoronaVac following a 3-shot vaccine schedule 28 days and 6 months apart. Following that, venous blood (3–5 ml) was collected from recipients at five time points: day 0 , day 30±3 (V2-1m), day 90±7 (V2-3m), and day 180±14 (V2-6m) after the second dose, and day 30±3 (V3-1m) after the third dose .The commercial detection kit iFlash-2019-nCoV NAb assay  was employed to measure the levels of IgG and IgM against SARS-CoV-2 spike glycoprotein (S) and nucleocapsid protein (N) by chemiluminescence immunoassay. Briefly, serum samples were allowed to form a complex with SARS-CoV-2 S- and N-protein antigen-coated paramagnetic microparticles, then an acridinium-ester-labeled ACE2 conjugate was added to competitively combine with the particles, forming another reaction mixture. The analyzer converted relative light units (RLUs) into an antibody titer (AU/mL) through a two-point calibration curve. An inverse relationship existed between the amount of SARS-CoV-2 NAb in the sample and the RLUs detected by the iFlash optical system. According to the manufacturer, titers of ≥10.0 AU/mL and ≥1.0 AU/mL are considered positive (or reactive) for IgG and IgM, respectively. IgG and IgM against SARS-CoV-2 receptor binding domain (RBD) were detected using a commercial ELISA kit . The positive cutoff values for RBD-specific IgG and IgM antibodies were defined as titers of ≥1.0 AU/mL. All tests were performed according to the manufacturer’s protocols .5 /ml cell suspension was added to the wells. The CPE (cytopathic effect) on VeroE6 cells was analyzed at 4 days post-infection. NT50  was used to show the neutralization titers. NT50 above 1:4 was defined as positive.The levels of neutralizing antibodies to live SARS-CoV-2 were assessed by the reduction in the cytopathic effect (CPE) in Vero cells with infectious SARS-CoV-2 strain 19nCoVCDC-Tan-HB01 (HB01) in a BSL-3 laboratory . Briefly2 for 1 hr. A 2×105 /ml BHK-21-ACE2 cell suspension was added to each well of the plate containing the sample/pseudovirus mixture, then the plate was incubated in a 37 °C and 5% CO2 cell incubator for 48 hr. Finally, the number of green-fluorescence-protein-positive cells per well was read with a porous plate imager . The results were determined by comparing the neutralized fraction using the following calculation: )×100% , Delta (B.1.617.2), and Omicron (B.1.1.529) using the pseudovirus-based virus neutralization test . Brieflye))×100% . At leasSex, age, BMI, and other clinical characteristics were collected for each vaccination recipient. We used the medians and interquartile ranges (IQR) for age, and numbers (percentages) for categorical variables. Specific binding antibodies against SARS-CoV-2  and neutralized fraction of SARS-CoV-2-neutralizing antibodies are presented as mean ± standard error (SEM). Neutralizing antibodies are presented as geometric mean titers (GMT), and their 95% confidence interval (CI) was calculated with Student’s t distribution on log-transformed data and then back-transformed. Comparisons of titer-level differences between the two groups were performed using the paired Student’s t-test. One-way analysis of variance (one-way ANOVA) was used to analyze the differences between the mean values at different timepoints. Correlations between NAb titers, neutralized fraction, and IgG/IgM levels were evaluated by Pearson’s correlation coefficient. Statistical tests were two-sided, and we considered p-values of less than 0.05 as statistically significant. All statistical analyses were conducted in SPSS 18.0  and GraphPad Prism 9 .We conducted a cross-sectional survey and recruited 1067 volunteers who had no vaccination or were vaccinated with one or two doses of CoronaVac in October 2020 or later in this multicenter study. Participants ranged in age from 18 to 59 years, with a median age of 40 years , and there was a balanced distribution of males (43.3%) and females (56.7%). Samples were collected at eight timepoints, including V-0 (n=91), V1-14d (n=125), and V1-28d (n=91) after vaccination with the first dose and V2-1m (n=100), V2-3m (n=110), V2-6m (n=160), V2-9m (n=190), and V2-12m (n=200) after vaccination with the second dose . Demogra2, and 33.3% had ≥1 underlying comorbidity (most commonly hypertension and diabetes)  males and 50 (56.6%) females with a median age of 64 years , 33.3% of whom had a BMI of ≥24.0 kg/miabetes) . The pariabetes) . None ofTo explore the dynamic changes in humoral immune responses to the inactivated COVID-19 vaccine, we first evaluated the recipients’ anti-S/N IgM and IgG development at different timepoints . The tit2=0.7364, p<0.001; R2=0.7170, p<0.001, S protein RBD binding to the angiotensin converting enzyme 2 (ACE2) receptor is a critical initial step in the entry of SARS-CoV-2 into target cells . We dete2=0.014, p=0.243), NAb titers and anti-RBD IgM , NAb titers and anti-S/N IgG , neutralized fraction and anti-S/N IgM , neutralized fraction and anti-RBD IgM ; whereas moderate correlations between NAb titers and anti-RBD IgG , NAb titer and neutralized fraction , neutralized fraction and anti-S/N IgG , neutralized fraction and anti-RBD IgG .Participants were tested with a live virus-based and pseudovirus-based neutralization assay. As depicted in With the dampening of antibody responses to the CoronaVac vaccine, we gave the cohort of 90 individuals booster immunizations up to 6 months after the second dose, and the antibody-titer-level distributions are shown in the violin plot in After the primary two doses and the third booster dose, a similar increasing trend was observed in the two neutralization test results . The GMTThe levels of antibodies grouped by age , sex, BMI, and chronic conditions at each monitoring point are presented in Mutations in the RBD may lead to a reduction in the antibody neutralization susceptibility of VOC . We furtInactivated vaccines have been widely used worldwide, mainly to reduce the COVID-19 severity and hospitalization rate and number of related deaths . HoweverPrevious studies have shown that antibody responses usually decline over time after an initial COVID-19 vaccination. Following vaccination with the Pfizer BNT162b2 vaccine, humoral responses were substantially decreased after 6 months among healthcare workers in Israel of 65 years of age or older, especially men . In addiWe also assessed the dynamics of antibody levels in a small prospective longitudinal cohort 6 months following two vaccination doses and found they were consistent with the above findings. Importantly, a booster injection around 6 months after the primary vaccination activated the anamnestic immunity and raised immune components (such as NAbs) to higher levels. Additionally, several factors, such as age group, sex, obesity, and chronic conditions affecting neutralizing antibody levels, were analyzed. We found that initial and booster-vaccine-elicited neutralizing antibody titers was weaker in older than younger adults, similar to the findings described in many other reports . Even soThe live SARS-CoV2 neutralizing antibody test has been used as a gold standard for evaluating vaccine immunogenicity in clinical trials and has shown correlations with protection from COVID-19 for real-world vaccinations . In our The Delta variant has eight mutations of the S protein, two of which are within the RBD, while there are 30 spike mutations in Omicron variant BA.1 . Our resHowever, there were some limitations to this investigation. First, the sample size in this study was based on practical considerations rather than statistical power calculations, and the distribution of age and sex were not very well balanced in the study. Second, vaccine efficacy was not calculated, as we did not compare the NAb titers generated by vaccination with those of convalescent COVID-19 patients or a serum standard panel in parallel. Third, we assessed only serum antibody responses, and further evaluations focusing on memory and cellular immunity are needed. Forth, we detected the neutralization activity to Delta and Omicron with pseudovirus-based neutralizing test, only calculated the fraction neutralized at 1:50 plasma dilution (%), not the NT50.In conclusion, our study suggests that vaccination against SARS-CoV-2 with two doses of CoronaVac can trigger humoral responses in the majority of vaccination recipients aged 18–59 years. Although binding and neutralizing antibodies were still detectable at 12 months post-vaccine, serum antibody levels tended to decrease over time, and Delta and Omicron variants may be able to more efficiently evade the antibodies induced by the inactivated vaccine with time. Despite the booster dose of inactivated vaccine can reverse the decrease of antibody levels to prime strain and heighten the cross immune response to Delta, it does not elicit potent neutralization against Omicron, which is circulating now. So, the optimization of the booster procedure such as heterologous boost immunization using viral-vector-, nucleic-acid-, and protein-based vaccines is necessary. This study presents important evidence that boosting with the Sinovac Coronavac inactivated vaccine would provide considerable protection from ancestral SARS-CoV-2 in terms of elicited neutralizing antibodies but would offer minimal protection against Omicron subvariants. The evidence supporting the claims of the authors is solid, although using a dilution series instead of one plasma dilution for Omicron neutralization would have strengthened the study. The work will be of very wide interest to the biomedical community and beyond, since it points to the need for a better booster vaccine in China. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, including Alex Sigal as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Neil Ferguson as the Senior Editor.Thank you for submitting your article "Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:Given the current shift in COVID-19 policy in China from Zero-Covid to minimal restrictions, a major infection wave is taking place. This paper shows that boosting with the Sinovac Coronavac inactivated vaccine would provide considerable protection from the ancestral virus and the no longer circulating Δ variant in terms of elicited neutralizing antibodies. But it would offer minimal protection against Omicron subvariants.This data  points to the need for a better booster vaccine in China. After careful consideration, the Reviewers agreed that given the time-sensitive nature of the data, the paper can be re-submitted without further experimental work. The authors should ensure that the following points are addressed:(1) The bottom line, that Coronavac does not elicit potent neutralization against Omicron, should be unequivocally stated.(2) There are multiple issues with the presentation of the work as outlined by both Reviewers which should be fixed in the revised manuscript. As an example, the meaning of "neutralization inhibition rate" in Figure 5 is critical to understand the figure but is hard to decipher without carefully reading the Materials and methods. The relevant information (e.g. that testing was done at a 1:50 plasma dilution) should be accessible in the figure . A more standard ID50 would be better if the authors have the serial dilution data.Reviewer #1 (Recommendations for the authors):While the paper is an important one, the major weakness is the way the pseudovirus neutralization assays were done. In addition, whether any of the participants were previously infected is unclear.(1) The pseudovirus neutralization assay is done only at the 1:50 concentration. This weakens the result and presents them in a way that is non-standard to the field. At least for the booster results, a standard dilution series should be performed and a dose-response curve fitted to obtain the ID50. The limit of detection should also be included, and be clearly presented for all figures.(2) It would be very useful to know what proportion of study participants were previously infected and if there are differences between the previously infected and uninfected individuals. This is clearly complicated by the fact that the vaccine is inactivated virus and therefore discrimination by the presence of anti-nucleocapsid antibodies will not work. However, any clinical record of infection could be used. If none, this should be stated.(3) Given the data, it is unclear how the authors can conclude on line 260 that: "protective capability of a primary vaccination series is enhanced following booster doses and optimization of the booster procedure" unless they are not talking about their study. The boost doesn't work as far as eliciting neutralizing antibodies against Omicron, which is what is circulating now, and this should be stated outright.Reviewer #2 (Recommendations for the authors):Line 115: 'critical' value. Did the authors mean threshold here?Lines 135-139 are unclear in terms of the exact correlations being tested for.Line 160 – may be better to use the term 'primary' course of vaccination.Line 177: I would not use the word unprecedented. Rather could say they have been used widely.Line 210-212: this does not make sense.The references omit some of the key papers in the field. Where possible the authors should cite primary sources eg for the emergence of omicron Viana et al., Nature. For comparative biology of spike between omicron and δ, there are a number of possibilities including https://doi.org/10.1038/s41586-022-04462-1, https://www.tandfonline.com/doi/full/10.1080/22221751.2021.2023329, https://doi.org/10.1038/s41586-022-04474-x, and others. Some of the papers also report an increased breadth of neutralisation against omicron with booster doses that should be included in citations and compared to results observed in this study with boosting. https://doi.org/10.1038/s41586-021-04389-z.In addition, the authors discuss the impact of age on response to vaccines but have not adequately cited papers on vaccine efficacy or in vitro neutralsiation / T cell responses in the elderly. This is clearly a key point for the Chinese population and needs further discussion, especially in light of recent developments in covid control policies.The rationale for using an assay that detects N and S antibodies together without distinguishing them is unclear and should be addressed. In my view, this is a weakness.Figure 4 should show data for Delta and Omicron. The data appear to be for WT only.Table 1: Please define how the positive rate was determined.Table 3: The 'positive rate' should be defined. Is it a GMT of >20 for example?Table S2: please define P1 and P2 in the table legend. There should be 95% CI or sd around the inhibition rate %.Table S3: The 'positive rate' should be defined.eLife. Your revised article has been evaluated by Neil Ferguson (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:The authors partially completed the referee corrections, and this paper does not require an additional round of review. However, the presentation of the work should be corrected before publication.(1) The most significant result of the study – that the inactivated vaccine booster does not elicit potent neutralizing antibodies against Omicron, should be stated in the abstract.(2) Title: "Evaluation of antibody kinetics and durability in health subjects…" should be changed to "Evaluation of antibody kinetics and durability in healthy…". Also, the term "subjects" is outdated, and the authors should consider using "individuals" or "participants".(3) Figure 2: that cross-sectional and not cohort (if that is the case) study participants were analyzed should be stated in the legend. If the participants at each time point are not the same, there should be no connecting lines between points .(4) Figure 3A-B: labels on graph missing "2" . Essential revisions:(1) The bottom line, that Coronavac does not elicit potent neutralization against Omicron, should be unequivocally stated.Thanks for your great suggestion. We have mortified the description in line 44-45, 347-350. Based on our data, we found Coronavac does not elicit potent neutralization against Omicron after the third dose as the editor' and reviewers' comments. Other studies draw similar conclusions. Li, et al. showed the neutralizing antibody GMTs against the Delta variant at day 14 after the homologous booster was 8.2  with 56% seroconversion . Fanglei Zuo, et al. showed the 90% neutralization titer (NT90) value against Β, Delta and Omicron VOC was 5, 5 and 5 respectively after homologous booster with inactivated vaccine . However, we considered the method only used the fraction neutralized at 1:50 plasma dilution (%) with pseudovirus-based neutralizing test was less powerful, so we did not emphasize this result unequivocally.(2) There are multiple issues with the presentation of the work as outlined by both Reviewers which should be fixed in the revised manuscript. As an example, the meaning of "neutralization inhibition rate" in Figure 5 is critical to understand the figure but is hard to decipher without carefully reading the Materials and methods. The relevant information (e.g. that testing was done at a 1:50 plasma dilution) should be accessible in the figure . A more standard ID50 would be better if the authors have the serial dilution data.Thanks for your great suggestion on improving the accessibility of our manuscript. We have corrected the y-axis label in figures and figure legends. The multiple issues by both Reviewers we have fixed in the revised manuscript and answered the comments point by point. Due to the few reagents of pseudovirus of Delta and Omicron, we could not detect all samples with the serial dilution. We tried to detect two serum samples by serial dilution showed in Table S2 as a limited reference, but it cannot work because of the different calculated method and observed outcome. Karaba, et al. detected with the similar method  showed that a cutoff of 20% ACE2 inhibition is associated with measurable live virus–neutralizing antibody, including versus VOCs .Reference1. Li J, Hou L, Guo X, Jin P, Wu S, Zhu J, et al. Heterologous AD5-nCOV plus CoronaVac versus homologous CoronaVac vaccination: a randomized phase 4 trial. Nat Med. 2022;28(2):401-9.2. Zuo F, Abolhassani H, Du L, Piralla A, Bertoglio F, de Campos-Mata L, et al. Heterologous immunization with inactivated vaccine followed by mRNA-booster elicits strong immunity against SARS-CoV-2 Omicron variant. Nat Commun. 2022;13(1):2670.3. Karaba AH, Zhu X, Liang T, Wang KH, Rittenhouse AG, Akinde O, et al. A third dose of SARS-CoV-2 vaccine increases neutralizing antibodies against variants of concern in solid organ transplant recipients. Am J Transplant. 2022;22(4):1253-60.Reviewer #1 (Recommendations for the authors):While the paper is an important one, the major weakness is the way the pseudovirus neutralization assays were done. In addition, whether any of the participants were previously infected is unclear.(1) The pseudovirus neutralization assay is done only at the 1:50 concentration. This weakens the result and presents them in a way that is non-standard to the field. At least for the booster results, a standard dilution series should be performed and a dose-response curve fitted to obtain the ID50. The limit of detection should also be included, and be clearly presented for all figures.Thanks for your great suggestion. We agree it is a weaken for our study only to calculate the fraction neutralized at 1:50 plasma dilution (%) with pseudovirus-based neutralizing test, not the NT50. We have discussed this limitation in the discussion. We designed the study early in 2021, when there were not many SARS-CoV-2 mutant strains. The primary objective was to evaluate the antibody kinetics and durability to WT after vaccinated with inactivated COVID-19 vaccine. Then with the emergence of Δ and Omicron, we added the detections with limited reagents. The limit of detection we have added in all figures with your professional suggestions.(2) It would be very useful to know what proportion of study participants were previously infected and if there are differences between the previously infected and uninfected individuals. This is clearly complicated by the fact that the vaccine is inactivated virus and therefore discrimination by the presence of anti-nucleocapsid antibodies will not work. However, any clinical record of infection could be used. If none, this should be stated.Thanks for your great suggestion. It is very interesting to compare the antibody levels induced by inactivated SARS-CoV-2 in previously infected and uninfected individuals. The participants we recruited were not previous or later SARS-CoV-2 infected. Because our study was conducted from May to December 2021, when China had taken the strict measures to prevent and control the epidemic. Our organization (Zhejiang CDC) had the recorded information of individuals if they had been infected SARS-CoV-2. Meanwhile, the study regions had no large outbreaks and epidemics during that period. We have mortified the descriptions in the methods and results (line 116 and 117).(3) Given the data, it is unclear how the authors can conclude on line 260 that: "protective capability of a primary vaccination series is enhanced following booster doses and optimization of the booster procedure" unless they are not talking about their study. The boost doesn't work as far as eliciting neutralizing antibodies against Omicron, which is what is circulating now, and this should be stated outright.Thanks for your great suggestion. The description was not accurate and we have mortified in line 347-350:“Despite the booster dose of inactivated vaccine can reverse the decrease of antibody levels to prime strain and heighten the cross immune response to Delta, it does not elicit potent neutralization against Omicron, which is circulating now. So, the optimization of the booster procedure such as heterologous boost immunization using viral-vector-, nucleic-acid-, and protein-based vaccines is necessary.”Reviewer #2 (Recommendations for the authors):Line 115: 'critical' value. Did the authors mean threshold here?Yes. Thanks for your great suggestion on improving the accessibility of our manuscript, we have corrected this word.Lines 135-139 are unclear in terms of the exact correlations being tested for.Thanks for your great suggestion, we have corrected the description in line 156-167:2 = 0.014, P = 0.243), NAb titers and anti-RBD IgM , NAb titers and anti-S/N IgG , neutralized fraction and anti-S/N IgM , neutralized fraction and anti-RBD IgM ; whereas moderate correlations between NAb titers and anti-RBD IgG , NAb titer and neutralized fraction , neutralized fraction and anti-S/N IgG , neutralized fraction and anti-RBD IgG .”“Correlation analysis showed poor correlation between NAb titers and anti-S/N IgM . Due to the weaker neutralized fraction to Delta and Omicron, we did note detected samples of other groups. The results showed in Figure 5.Table 1: Please define how the positive rate was determined.According to the manufacturer of kits, the concentration anti-S/N antibodies≥10.0 AU/mL (IgG) and ≥1.0 AU/mL (IgM) are considered positive (or reactive); for anti-RBD antibodies, the positive was defined as concentration≥1.0 AU/mL. The positive rate was percent of numbers of positive samples/ total detected samples. We have added the description in the table legends. Thanks for your great suggestion.Table 3: The 'positive rate' should be defined. Is it a GMT of >20 for example?The seropositivity rate is when positive titer of NT50 is above 1:4 and descripted in the methods. Thanks for your great suggestion, we have added the description in the table legends.Table S2: please define P1 and P2 in the table legend. There should be 95% CI or sd around the inhibition rate %.Thanks for your great suggestion. We have added the description in the table S2 legends. P1 and P2 means serum sample of person1 and person2. The samples were conducted with the serial dilution from 1:100 and tested with pseudovirus-based neutralization. We only detected with 1 complex well that 95% CI or sd around the inhibition rate % were valueless.Table S3: The 'positive rate' should be defined.We have added the description in the table S3 legends. Thank you very much for your valuable revision suggestions.The authors partially completed the referee corrections, and this paper does not require an additional round of review. However, the presentation of the work should be corrected before publication.(1) The most significant result of the study – that the inactivated vaccine booster does not elicit potent neutralizing antibodies against Omicron, should be stated in the abstract.Thanks for your great suggestion. We have mortified the description in line 44-45, 347-350.(2) Title: "Evaluation of antibody kinetics and durability in health subjects…" should be changed to "Evaluation of antibody kinetics and durability in healthy…". Also, the term "subjects" is outdated, and the authors should consider using "individuals" or "participants".”Thanks for your great suggestion. We have corrected the title to “Evaluation of antibody kinetics and durability in health individuals vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China(3) Figure 2: that cross-sectional and not cohort (if that is the case) study participants were analyzed should be stated in the legend. If the participants at each time point are not the same, there should be no connecting lines between points .Thanks for your great suggestion on improving the accessibility of our manuscript. We have corrected in the Figure 2.(4) Figure 3A-B: labels on graph missing "2" .Thanks for your great suggestion. It was my mistake and we have corrected in the Figure 3A-B.


There is a need for reliable and valid screening tools that assess depressive symptoms in adolescents in Pakistan. To address this need, the present study examined the psychometric properties and factor structure of a Sindhi-translated and adapted version of the child-report Mood and Feelings Questionnaire (MFQ-C) and the Short Mood and Feelings Questionnaire (SMFQ-C) in a community sample of adolescents living in Matiari, Pakistan. Questionnaires were translated into Sindhi and administered by study psychologists to 1350 participants  9.0 to 15.9 years old. Measurement structure was examined using confirmatory factor analysis. Internal consistency was estimated, and convergent and divergent validity were explored using subscales from the Strengths and Difficulties Questionnaire and the Screen for Child Anxiety Related Emotional Disorders. The unidimensional structure of the MFQ-C was found to be adequate, but a four-factor structure comprising core mood, vegetative, cognitive and agitated distress symptoms best fit the data . The original unidimensional structure of the SMFQ-C was supported . The MFQ-C and the SMFQ-C respectively showed excellent (α = 0.92) and good internal consistency (α = 0.87) as well as satisfactory construct validity with some differences observed across the MFQ-C subscales. The SMFQ-C and the adapted MFQ-C appear to be reliable and valid measures of depressive symptoms among early adolescents living in rural Pakistan. Both total and subscale scores can be derived from the MFQ-C to assess general and specific dimensions of depressive symptoms in this population. Depression in youth is common worldwide and has been identified as one of the leading causes of disability among those 10- to 24- years old . Youth wPakistan is classified as an LMIC and is the sixth-largest country in the world, with youth between the ages of 10 to 19 years old accounting for approximately 23% of the total population , 7. In aDespite the need for mental health care, in Pakistan, the ratio of psychiatrists per 100,000 people is 0.18, which is much lower than the world median ratio of 1.27 . FurtherMost existing screening tools for youth depression originate from high-income countries (HICs), and few psychometric studies have been conducted in LMICs . HoweverDSM-III-R, in addition to several items of clinical relevance related to loneliness and feeling unloved [The Mood and Feelings Questionnaire (MFQ) is one of the most useful tests for screening childhood depression in children and adolescents . It has  unloved  but has  unloved , 32. The unloved . Regardi unloved , 28, 33. unloved –36. Alth unloved –39. As s unloved .a = .92), convergent validity with related measures of depression , and good test-retest reliability [α = .84) and adequate convergent validity with the Spence Children’s Anxiety Scale-Parent version [To our knowledge, only two studies have examined the psychometric properties of the MFQ-C (long and short forms) in community samples of adolescents living in LMICs. In Thailand, the full-form MFQ-C was recently validated in a school-based study of youth 12 to 18 years old. The Thai MFQ-C showed excellent internal consistency  and males (10.0 to 15.9 years old) to account for variation in the onset of puberty. Several steps were taken to ensure that the sample was representative of the population of Matiari. Briefly, data regarding age, sex (assigned at birth), and the number of occupants in each household obtained from a companion study were used in the selection process. Using these data, computer-assisted random sampling was employed on 53,000 households within the Lady Health Workers catchment population of 26 health facilities in the Matiari District [The primary objective of the District . If housInclusion criteria for the principal study specified that participants must be within the age ranges of the study, and their birthmothers must be available and cognitively able to participate. Female participants could not currently be or previously have been pregnant. Lastly, participants with chronic or genetic illnesses known to impact growth  were excluded. For the present study, participants were also excluded if they had no responses to any MFQ items. Ethics approval for the principal study was obtained from Aga Khan University, Pakistan, and The Hospital for Sick Children, Canada. Ethics approval for the present study was also granted by the Centre for Addiction and Mental Health Research Ethics Committee, Canada.Written consent from legal guardians and assent from participants were obtained following standard procedures . Mental “I felt miserable or unhappy”) on a 3-point Likert scale: 0 “not true,” 1 “sometimes true,” 2 “true.” Total scores for the MFQ typically range from 0 to 66. Due to cultural sensitivities, four suicidality items from the original MFQ-C were administered only to participants who were deemed at-risk for self-harm. Therefore, the psychometric properties of our modified version of the MFQ-C was examined considering the remaining 29-item scale, with scores ranging from 0 to 58. Moreover, one school-related item (“I didn’t have any fun in school”), was not administered to adolescents not attending school and was conservatively coded as “0” for those participants. The Short Mood and Feelings Questionnaire (SMFQ-C) consists of 13-items from the MFQ-C that assess affective and cognitive symptoms of depression [The original MFQ-C is a 33-item questionnaire designed to assess depressive symptoms in children and youth ages 8 to 18 . Respondpression , with toThe Strengths and Difficulties Questionnaire (SDQ) is a 25-item questionnaire which has been originally validated among children 4 to 16 years old and contains five subscales: emotional symptoms, conduct problems, hyperactivity, peer problems, and prosocial behaviour [ehaviour , 43. Higehaviour .The Screen for Child Anxiety Related Emotional Disorders-child version (SCARED-C) was used to assess symptoms of anxiety and its expected correlation with depressive symptoms. It has been validated for use in children 8 to 18 years old and consists of 41 items relating to five distinct subscales: separation anxiety, panic/somatic symptoms, social anxiety, generalized anxiety, and school avoidance [“I am nervous”). Adolescents were asked to rate items on a 3-point Likert scale: 0 “not true or hardly ever true”, 1 “somewhat or sometimes true”, 2 “very true or often true”. The SCARED-C has not previously been validated in Pakistan, but has shown adequate face and content validity, and good internal consistency in a community sample of rural youth living in India [voidance , 45. Itein India .α = 0.05. The data were assessed for missing observations. Descriptive analyses for demographic variables and scale items were conducted, including examining correlations . The Kaiser-Meyer-Olkin (KMO) measure of sample adequacy was used to assess whether the sample was adequate for factor analysis (KMO ≥ 0.60 is acceptable) [All analyses were conducted in R studio . The significance threshold was set at eptable) .I ate more than usual”, “I did not want to see friends”, and “I worried about aches and pains”). Moreover, one item originally included in Jeffreys et al. (2016)’s solution  was specific to the MFQ parent version. As this item is not included in the MFQ-C, it was not considered in the present analysis. Regarding the SMFQ-C, we considered the unidimensional solution supported by previous studies [The factor structure and psychometric properties of the modified MFQ-C and the SMFQ-C were assessed using confirmatory factor analyses (CFA). Due to the ordinal nature of the MFQ scale items, the mean-and-variance adjusted weighted least squares (WLSMV) estimator was used . For the studies .2 /df) was reported for each model but the χ2 test was not used to assess model fit due to its sensitivity to large sample sizes [2 were assessed for evidence of measurement invariance [Item factor loadings below 0.32 were not interpreted and a threshold of 0.70 was used to characterize items with high factor loadings . Model fle sizes . Subgrouvariance , 51.α-i) were also assessed. Corrected item-total correlations were considered adequate when equal or higher than 0.30 [To evaluate internal consistency, which provides an indication of the extent to which the items of a scale measure the same construct . Cronbachan 0.30 .Convergent and divergent validity were examined using Spearman’s rank correlations between the MFQ-C/SMFQ-C and other scales. Depression symptoms often overlap with anxiety and emotional symptoms. All have been shown to cluster together on the larger construct of symptoms of internalising disorders, separately from symptoms of externalizing disorders , 55. In Only one participant was excluded from our analyses due to missing responses to all MFQ items  years, 12.8 (SD = 1.6) years for males, and 12.0 (SD = 1.7) years for females. The majority of participants attended school and lived in rural areas. Compared to males, females were younger, were less likely to attend school but more likely to live in an urban area. Their mothers were also slightly younger and they were more likely to live in a Muslim family  for the total sample and ranged from 0 to 50. Mean total scores were significantly higher in females  than males . The mean total score on the SMFQ-C was 2.5 (SD = 3.4) for the full sample and ranged from 0 to 24 with females also scoring significantly higher  than males . Total score distributions for the full sample were right-skewed . Spearman’s correlations between items are available in Fig B in The mean total score on our modified 29-item MFQ-C scale was 5.6 (I didn’t have any fun in school”) to 0.97  . In a sensitivity analysis conducted in the subgroup of participants who attended school, this item loaded higher but still had the lowest factor loading (0.46), and there was minimal change in model fit indices. Finally, the unidimensional model for the SMFQ-C also showed excellent fit , with all factor loadings being greater than 0.49  . Howeverslowly”) . Again, han 0.49 .2 /DF across the configural, metric, and scalar models were non-significant and models had acceptable fit for males and females  and the corrected item-total correlations were adequate (≥ 0.30) for all items except for: “I didn’t have any fun in school (r = 0.23) and “I slept a lot more than usual” (r = 0.24).Cronbach’s alphas and corrected-item total correlations are presented in α = 0.87 and α = 0.81) and acceptable for the ‘core mood’ and ‘agitated distress’ subscales (respectively α = 0.62 and α = 0.66). Again, low item-total correlations were found for the items “I didn’t have any fun in school” (r = 0.17) on the ‘cognitive’ scale and “I slept a lot more than usual” on the ‘vegetative’ subscale (r = 0.24). Removal of these items only slightly improved the internal consistency of their corresponding subscales. In sensitivity analyses conducted among adolescents attending school, the item-total correlation for the item “I didn’t have any fun in school” remained modest on the unidimensional scale (r = 0.31) and the “vegetative” subscale (r = 0.28).Regarding MFQ-C subscales, internal consistency was good for the ‘cognitive’ and the ‘vegetative’ subscales (respectively α = 0.87). Item-total correlations ranged from 0.36 (“I cried a lot”) to 0.67 (“I hated myself”) and Cronbach’s alpha when items were removed remain comparable (α-i between 0.85 and 0.87).The internal consistency of the SMFQ-C was good  scores and scores on the SDQ-emotional symptoms and on the SCARED-C subscales . Similarρ ≤ -.10). However, no significant correlation was found between the SDQ-prosocial behaviour and the MFQ-C cognitive symptoms subscales. Surprisingly, the MFQ-C total and subscale scores, as well as the SMFQ-C scores, demonstrated low-to-moderate correlations with scores on the SDQ-hyperactivity and SDQ-conduct problems subscales (.08 ≤ ρ ≤ .39). The magnitude of the correlations varied greatly across the MFQ-C subscales, with a moderate correlation observed for core mood symptoms and low correlations observed for the vegetative, cognitive and agitated distress subscales.In terms of divergent validity, the MFQ-C scale, its core mood, vegetative, and agitated distress subscales and the SMFQ-C scale demonstrated a small but significant negative correlation with the SDQ-prosocial behaviour subscale  [α = 0.62) was lower than previously observed (α = 0.78) [The reliability of the full-scale MFQ-C in this sample was similar to previously reported estimates from other LMICs (90–0.92) , 32. Our = 0.78) . This diM = 8.67, SD = 5.61) [Our results provide strong support for the unidimensional structure of the SMFQ-C and its reliability and validity in a sample of youth in Pakistan. The internal consistency and unidimensional factor structure of the SMFQ-C was in accordance with results obtained in past studies conducted in LMICs , 58. The = 5.61) . This di = 5.61) .The convergent validity of our modified MFQ-C  and the SMFQ-C was supported. The observed positive correlations with scores on the SDQ-emotional symptoms subscale are consistent with past research examining the MFQ-C and MFQ-P , 28. SimRegarding divergent validity, surprisingly significant correlations were found between scores on the MFQ-C , the SMFQ-C, and scores on the SDQ-conduct problems and SDQ-hyperactivity subscales. However, the associations observed between depressive symptoms and conduct problems are in agreement with previous results obtained in community samples from HICs and could be explained by the overlap of symptoms of both conditions, by their mutual influence on one another, or by shared underlying etiological factors such as socioeconomic factors . In LMICI ate more than usual”, “I worried about aches and pains” and “I did not want to see friends”. Modest item-total correlations were found for “I ate more than usual” and “I worried about aches and pains” when assessing the unidimensional structure of our MFQ-C , with similar findings also noted in a Danish school-based study [I ate more than usual” was also low (r = 0.20) [The main strength of our work lies in the use of a representative sample and of standardized methods that limit selection and information biases and allow us to generalize our results to the population of adolescents living in Matiari. Nevertheless, our findings should be considered in light of several limitations. Firstly, because our modified version of the MFQ-C excluded four suicidal items, the total scores were computed by summing the score of 29 items, rather than 33. As such the mean total MFQ-C score obtained in our sample cannot be compared to scores obtained in other studies. Secondly, in accordance with Jeffreys et al. (2016)’s analysis, our four-factor solution did not include the following three items: “ed study . Further = 0.20) . HoweverOverall, both the Sindhi MFQ-C and SMFQ-C appear to be reliable measures of depressive symptoms in early adolescents living in rural Pakistan. While the unidimensional structures of the MFQ-C and SMFQ-C provide a global measure of depressive symptom severity, the symptom-specific subscale scores of the MFQ-C allow for the assessment of specific dimensions of depressive symptoms. The brevity of the SMFQ-C further emphasizes its usefulness in low-resource settings, where limited time and/or trained staff prevent long-form questionnaires from being administered. Our findings also support the use of these instruments in future population-based studies, which may contribute to the surveillance and the identification of covariates of adolescent depressive symptoms in rural Pakistan. Research regarding reasonable cut-off scores that indicate probable depression in this population would provide further insight into its usefulness as a diagnostic or screening tool. More generally, the MFQ questionnaires may also be used in other LMIC populations that share similar characteristics and cultures.S1 FileFig A. Participant Flow-chart. Fig B. Spearman’s Correlations between items from the Mood and Feelings Questionnaire—child version. Table A. Measurement Invariance Analysis by Sex of the Child Report Version of the 26-item Four Factor Mood and Feelings Questionnaire (MFQ-C) and the Short Mood and Feelings Questionnaire (SMFQ-C)—child versions. Table B. Factor loadings for the four-factor and unidimensional structure of the adapted Mood and Feelings Questionnaire- child version and the unidimensional structure of the Short Mood and Feelings Questionnaire-child version.(DOCX)Click here for additional data file.S2 File(PDF)Click here for additional data file.S3 File(DOCX)Click here for additional data file.


TRIM56 expression levels and severe infections of COVID-19 between the Alpha, Delta and Omicron BA.5 variants.The present study aimed to determine a correlation between differential TRIM56 gene expression were determined using a qPCR.This study was performed on 330 COVID-19 patients, including 142 with severe and 188 with mild infections, as well as 160 healthy controls. The levels of TRIM56 gene showed significantly lower mRNA expression in the severe and mild groups compared with healthy individuals. Our finding indicated the high and low reduction of TRIM56 mRNA expression in Delta and Omicron BA.5 variant, respectively.Further research is needed to characterize the impact of TRIM proteins on the severity of COVID-19. TRIM56, was linked to how poorly people became with COVID-19. The study looked at the blood samples of 330 patients and found that COVID-19 patients had less TRIM56 than healthy people, especially those who were particularly ill.Scientists looked at a protein called TRIM that helps fight viruses to see if a specific TRIM protein,  et al. discovered that the TRIM56 gene, which plays a crucial role in the body's immune response to viruses, is likely associated with severe COVID-19 infections.#Tavakoli  As the first line of defense against invading pathogens, the host innate immune system recognizes pathogen-associated molecular patterns (PAMPs) uisng pattern recognition receptors (PRRs) encoded by innate immune cells . The tolPro- and anti-inflammatory responses during viral disease progression can result in apoptosis in endothelial and epithelial cells in the lung tissue due to a high and uncontrolled level secretion of cytokines like IL6, IL8 and TNF-a, known as a ‘cytokine storm’ . CytokinCRP is an acute-phase protein that is produced by the liver in response to inflammation and is considered a predictive indicator for severe inflammation in progressive respiratory failure by SARS-CoV2, MERS and SARS-CoV . PreviouThe tripartite motif (TRIM) protein family is the most extensive subfamily of the really interesting new genes (RING)-type E3 ubiquitin ligase family with E3 ubiquitin ligase activity in the N-terminal RING domain . A wide TRIM56 gene is a stimulator of interferon genes (STING) that enhances the antiviral potential of IFN-I and has been found to positively regulate the TLR3-mediated IFN pathway [The  pathway ,21. TLR3 pathway ,22. Unde pathway . The act pathway ,25. TRIM pathway ,27.It has been found that some viral proteins can deactivate host restriction factors. This ability of viruses can be improved by the evolutionary arms race between host and virus, helping the virus escape from the host immune system with new variants resulting in a pandemic or endemic infectious disease, such as has been the case with SARS-CoV-2 and COVID-19 ,29.TRIM56 gene can be a possible regulator of infection with SARS-CoV-2 by moderating the innate immune response and inhibiting the replication of SARS-CoV-2. Therefore, we evaluated the mRNA level of TRIM56 gene in our study groups of COVID-19 patients.In view of this, we propose that This study included 300 patients with COVID-19 (severe and mild infection) and 160 uninfected subjects. Mild infection was defined as light clinical respiratory symptoms and fever without pneumonia, while severe infection was considered pneumonia, acute respiratory failure and an oxygen saturation of less than 92%. Patients with severe infections were hospitalized in the intensive care unit. Samples from uninfected controls were gathered at the Pasteur Institute of Iran (PII) before the COVID-19 pandemic.The blood samples of COVID-19 patients were taken from November 2020 to February 2022, one week post the initiation of infection. During this time period, the most prevalent subtypes of the SARS-CoV-2 virus in Iran were the Alpha, Delta and Omicron BA.5 variants.In this study, COVID-19 patients had no comorbidities or underlying disease such as diabetes, allergic diseases, chronic respiratory diseases, heart diseases or cancer.The laboratory parameters, including lipid profiles, liver enzymes profile, fasting blood glucose (FBS), C-reactive protein (CRP), white blood cells (WBC), platelets, erythrocyte real-time PCR Ct values, creatinine, sedimentation rate (ESR), uric acid, and 25-hydroxyvitamin D, were extracted from the patients' records.The messenger RNA (mRNA) of whole blood samples was extracted using RNA lysis buffer  according to the supplier's protocol. The concentrations and purity of RNA were quantified by a Nanodrop spectrophotometer and RNA was stored at -80°C.TRIM56 were 5′-CAGCTCTGGCTAGTTCTCAC-3′ and 5′-TCCTTCTAGTCTTCTGAGGC-3′. The housekeeping gene was and for hypoxanthine phosphoribosyltransferase 1 (HPRT1). A total of 1 μg of mRNA treated by the DNaseI enzyme  was reverse transcribed into cDNA according to the manufacturer's instructions .The design stage of primers was performed by OligoAnalzer online tool in the exon-exon junction approach. The Refseq RNA sequences were taken from GenBank at National Center for Biotechnology Information (NCBI), and the predicted melting temperature was considered around 60°C. The primer sequences for TRIM56 was quantified by quantitative real-time PCR (qPCR) in two technical replicates  using SYBR green qPCR master mix . The cycling profile included 15 min at 95°C as the holding temperature followed by 15 sec at 95°C and 30 sec at 60°C for 40 cycles with the melting measure program at the end. The reference gene was selected out of four candidate's gene . The HPRT1 was used as the most stable housekeeping gene  in blood samples according to the ranking of a web tool named RefFinder [-ΔΔCT method) was used based on cycle threshold values.The relative level of TRIM56 on the COVID-19 susceptibility, the curve-receiver operating characteristic analysis (ROC) and the area under curve (AUC) were performed. Spearman rank correlation analysis was used for determining the correlation between different variables. The statistical level of significance was considered p < 0.05.The qPCR results were analyzed statically using SPSS for Windows version 22.0. . The median and interquartile ranges (IQR) of non-parametric data were obtained. For assessing the normality of variables, the Shapiro-Wilk test was performed. Pearson's Chi-square test was used to analyze qualitative variables and Mann-Whitney test was used for quantitative variables. To assess the effect of the expression of The comparative analysis of clinical features and laboratory results of COVID-19 patients is summarized in TRIM56 mRNA in the severe group demonstrated a reduction in comparison to the uninfected control group (p < 0.0001). The mild group showed a reduction (median: -0.18) (p = 0.0014) versus the control group, but greater expression compared with the severe group (median: -0.53) (p < 0.0001)  A. AdditiCOVID-19 B.TRIM56 mRNA expression when patients were infected with the Delta versus the Omicron BA.5 variant (p < 0.0001). Infection with the Delta variant demonstrated lower levels of TRIM56 mRNA expression when compared with both the Alpha and Omicron BA.5 variants (p < 0.0001). Infection with the Alpha variant was associated with a reduction in TRIM56 mRNA expression (median: -0.15) (p < 0.0001) versus the Omicron BA.5 variant   .TRIM56 mRNA levels of COVID-19 patients. Ct values were positively correlated with the expression of TRIM56. Lower Ct values indicating higher loads of viral RNA showed a significant relationship with lower levels of TRIM56 expression   .TRIM56 gene expression , as shown in The study conducted a multivariate logistic regression analysis to identify the factors that were associated with the severity of COVID-19 infection. The results indicated that several factors were significant predictors of severity. These factors included mean age , LDL , HDL , uric acid , creatinine , ALT , ESR , 25-hydroxyvitamin D , CRP  real-time PCR Ct values , and TRIM56 expression. We also wanted to find the relationship between TRIM56 expression and two clinical laboratory factors, including the CRP marker and Ct value of the qPCR test.We evaluated whole blood samples of COVID-19 patients to assess the correlation between the severity of SARS-CoV-2 and TRIM56 gene was identified in this study. Alteration in the expression of cytokines and immune mediators in SARS-CoV-2 infection results in cytokine storm and systematic inflammation in severe cases, which is related to high mortality in COVID-19 [TRIM56 gene in viral infection may lead to the unregulated generation of IFN and cytokines.A significant correlation between increased CRP value and decreased COVID-19 . CytokinCOVID-19 . Recent COVID-19 ,35. SpecCOVID-19 . Plus, eCOVID-19 . On the COVID-19 ,20. ReduTRIM56 was expected to be greater in SARS-CoV-2 infection according to previous studies [TRIM56 mRNA in severe patients compared with healthy controls and patients with mild COVID-19. Wang et al. reported in 2011 that TRIM56 has an innate antiviral effect against bovine viral diarrhea virus (BVDV), an RNA virus with positive-strand, in an in vitro study. They showed that TRIM56 interacted with the BVDV N-terminal protease via its C-terminal and blocked the function of this protein in BVDV with interferon regulatory factor 3 (IRF3). However, a large deletion in the N-terminal of TRIM56 had an important effect on the folding of the protein and its interaction with the protease of BVDV [et al. also confirmed that a decline in TRIM56 expression level leads to the replication of BVDV [TRIM56 in human hepatoma (Huh7) cells did not restrict the repetition of the hepatitis C virus (HCV) [TRIM56 inhibited viral replication by blocking viral RNA synthesis [TRIM56 for IAV and SRAS-CoV-2 in A549 cells. Analysis of lung tissue samples of COVID-19 patients also reported a decrease in TRIM56, though this was not significant (P 0.09) [TRIM56 gene has some polymorphisms in regulatory sequences that affect its expression in COVID-19 patients, or that SARS-CoV-2 has a genetic mutation that can facilitate the inhibition or reduction of the expression of TRIM56 gene. The impact and antiviral mechanisms of TRIM56 gene in COVID-19 need further investigation.The expression of  studies . In cont of BVDV . Moreove of BVDV . Wang et of BVDV . The antus (HCV) . Furtherynthesis . Plus, Tynthesis . It has ynthesis . In addi(P 0.09) . It is pTRIM56 in patients. Ct value of the qPCR test is considered a simple clinical marker of COVID-19 infection as it indicates viral RNA load [TRIM56 mRNA in patients. We also showed a significant reduction of TRIM56 gene expression in severely ill patients. TRIM56 has a restrictive role in the replication of RNA viruses like HCoV-OC43, so it is likely that TRIM56 similarly interacts with SARS-CoV-2 and as a result, the reduction of TRIM56 observed in patients with severe COVID-19 may be associated with the superior viral load in these patients.We also assessed the correlation between the Ct value of the qPCR test and the mRNA expression level of RNA load ,44. TherRNA load . In thisTRIM56 gene expression. Higher levels of CRP, lower levels of TRIM56 gene expression and lower Ct values were associated with an increased risk of severe disease. Studies have shown that COVID-19 severity may be linked to elevated liver enzyme levels, which may indicate liver injury. This injury is characterized by abnormal liver enzyme levels and slightly increased bilirubin concentrations [ACE2 expression, thereby contributing to the severity of COVID-19 [ACE2 [ACE2 expression have been linked to more severe COVID-19, it remains unclear how much vitamin D may actually benefit those with the disease. Further studies are needed to develop effective treatment strategies for COVID-19 across different levels of severity [The multivariate logistic regression analysis of results showed that several factors were significant predictors of the severity of COVID-19. These factors include mean age, LDL, HDL, uric acid, creatinine, ALT, ESR, 25-hydroxyvitamin D, CRP, real-time PCR Ct values and trations ,47. Althtrations . Previoutrations . Patienttrations . Interestrations . AccordiCOVID-19 ,53. 25-h19 [ACE2 . Becauseseverity . Many paseverity . Finallyseverity .In agreement with our previous studies ,18,19, tTRIM56 gene in blood samples. Large-scale research on different aspects are recommended to confirm the findings mentioned above. It's important to note that these findings were observed in the specific population studied and may not be generalizable to other populations.Few researchers have reported on the activity of TRIM proteins during SARS-CoV-2 infection. Our study provides a clue to the TRIM proteins' role in COVID-19 and focuses on expression of the TRIM56 mRNA in the severe group showed a significant reduction in comparison with the uninfected control group.The expression level of The mild group represented a meaningful decrease versus the control group and had upregulation compared with the severe group.TRIM56 gene expression was 0.786, implying that the expression of this gene is frequently required for the severity of COVID-19.The area under curve-receiver operating characteristic analysis value for TRIM56 mRNA expression was shown in Alpha, Delta and Omicron BA.5 variants, respectively.Our finding indicated the high and low reduction of TRIM56 in patients had a meaningful correlation with CRP value and viral RNA load with r = -0.26 and r = 0.27 respectively.Expression mRNA level of


The COVID-19 pandemic and its impact on healthcare services is likely to affect birth outcomes including the delivery mode. However, recent evidence has been conflicting in this regard. The study aimed to assess changes to C-section rate during the COVID-19 pandemic in Iran.This is a retrospective analysis of electronic medical records of women delivered in the maternity department of hospitals in all provinces of Iran before the COVID-19 pandemic  and during the pandemic . Data were collected through the Iranian Maternal and Neonatal Network (IMAN), a country-wide electronic health record database management system for maternal and neonatal information. A total of 1,208,671 medical records were analyzed using the SPSS software version 22. The differences in C-section rates according to the studied variables were tested using the χ2 test. A logistic regression analysis was conducted to determine the factors associated with C-section.p = .001). The rates for preeclampsia (3.0% vs 1.3%), gestational diabetes (6.1% vs 3.0%), preterm birth (11.6% vs 6.9%), IUGR (1.2% vs 0.4%), LBW (11.2% vs 7.8%), and low Apgar score at first minute (4.2% vs 3.2%) were higher in women who delivered by C-section compared to those with normal delivery (P = .001).A significant rise was observed in the rates of C-section during the pandemic compared to the pre-pandemic (52.9% vs 50.8%; The overall C-section rate during the first wave of COVID-19 pandemic was significantly higher than the pre-pandemic period. C-section was associated with adverse maternal and neonatal outcomes. Thus, preventing the overuse of C-section especially during pandemic becomes an urgent need for maternal and neonatal health in Iran. How has the first wave of COVID-19 pandemic affected the C-section rate in Iran?The COVID-19 pandemic and its impact on healthcare services may have adverse impacts on maternal and perinatal health including the delivery mode.The overall C-section rate during the first wave of COVID-19 pandemic was significantly higher compared to the pre-pandemic period.The Coronavirus disease 2019 (COVID-19) pandemic has affected the health of pregnant women globally . DespiteAlthough, the increased risk for C-section has been reported during the pandemic, this risk appears to be limited to women with severe or critical disease and being infected in third-trimester . AdverseTo the best of our knowledge, there is little evidence regarding the rate of C-section during the first wave of COVID-19 in Iran. Since improving the maternal outcomes is a global priority, especially during a pandemic, the present nationwide study was conducted to assess how the first wave of COVID-19 pandemic has affected the C-section rate in all provinces of Iran.The study is part of a comprehensive national study on reproductive health outcomes during the COVID-19 pandemic which was conducted in 2020 in Iran. We conducted a retrospective analysis of electronic medical records of women delivered in the maternity department of hospitals in all provinces of Iran before the COVID-19 pandemic  and during the pandemic , covering the first wave of the pandemic. To collect data, we used a data retrieval form on socio-demographic and fertility-related characteristics and the reproductive health outcomes through the Iranian Maternal and Neonatal Network (IMAN) that is a country-wide electronic health record database management system for maternal and neonatal information. In this study, outcome measures were C-section rates, and perinatal outcomes of C-section. Data were exported to Excel® and statistical analyses were performed using the SPSS software version 22.P value less than 0.05 were considered statistically significant.Comparisons between pre and intra-COVID-19 pandemic involved six months of the same period of the year to take into account the possible influence of seasonal differences. The differences in C-section rates according to the studied variables were tested using the χ2 test. A logistic regression analysis was conducted to determine the factors associated with C-section. A Ethical approval for the research project was obtained from the ethics committee of the National Institute for Medical Research Development (Code: IR.NIMAD.REC.1399.076). All methods were performed in accordance to the Declaration of Helsinki. Given that we only used the women’s medical records and were not in touch with any women, it was not possible for us to obtain informed consent from the subjects. However, to ensure confidentiality, no participant was recorded by name, and the results were only reported in groups.A total of 1,208,671 medical records were analyzed in the study with 624,521 (51.7%) before the COVID-19 pandemic and 584,150 (48.3%) during the pandemic. Table p = 0.001). Figure p = 0.001).The characteristics of women with C-section compared with those with normal delivery during the pandemic and pre-pandemic periods are presented in Table P = 0.001), the mother’s education level of secondary school (P = 0.001), abortion (P = 0.001), gestational age < 37 weeks (P = 0.001), and birthweight < 2500 gr (P = 0.001) and > 4000 gr (P = 0.001) were associated with higher chances of C-section delivery during the pandemic and pre-pandemic periods . The multiple logistic regression analysis showed that preterm birth (P = 0.001), gestational diabetes (P = 0.001), preeclampsia (P = 0.001), IUGR (P = 0.001), LBW (P = 0.001), and 1-min Apgar score < 7 (P = 0.001) were associated with higher chances for C-section delivery.Pregnancy outcomes of women with C-section delivery compared with those with normal delivery during the pandemic and pre-pandemic periods are presented in Table The findings of this study revealed an overall significant rise in the C-section rate from 50.8% in the pre-pandemic period to 52.9% during the first wave of COVID-19 pandemic, and the rates were increasing over time. Similarly, a study by Bhatia et al. from England showed a rise in the overall C-section rate during the pandemic (28.3% to 29.7%) . Iran haAs of 28 March 2020, Iran reported 35,408 confirmed cases of COVID-19 and 2517 total associated deaths, and ranked 7th in the list of confirmed cases globally. Therefore, the COVID-19 lockdown was imposed across the country in March and April 2020 .Although repeated C-sections and fetal distress were the two top indications for C-section in our study, C-section on maternal request increased during the pandemic. Also, 13.4% of C-sections had no indications. These might be normal pregnancies which ended in C-sections without medical indications and on maternal request. Li et al. also reported an increase in C-section on maternal request during the COVID-19 pandemic . GloballIranian women with C-Section differed from those with normal delivery in some variables. They were more likely to be older, primiparous, with lower gestational age, and have newborns with LBW or macrosomia. Higher maternal age , 18 and The adverse effects of C-section delivery on maternal and neonatal outcomes have been well documented . We obseThe main strength of this study can be its large size with including almost all births in urban health centers over two periods of six months, covering the first wave of the COVID-19 pandemic, allowing us to generalize the results to the rest of Iran. However, using registered data for research can be seen as a limitation. We were not able to use the Robson’s classification because we analyzed only the data registered on the IMAN from February 30 to August 30, 2019 and from February 30 to August 30, 2020, and data on some variables required for Robson’s classification (such as presentation) were not available within this time period. Our results were only for the first wave, and further research is needed to target the impacts of the following waves of the pandemic on the rates of C-section. Moreover, due to the nature of the data, the adverse pregnancy outcomes cannot be considered causal since the outcomes may be related to the medical reasons for the C-section , 30.The C-section rate during the first wave of COVID-19 pandemic was significantly higher than the pre-pandemic period. Results from our study provide evidence that the COVID-19 pandemic has substantially affected C-section practices in hospitals, and challenged obstetric settings in their tendency towards C-section. Our findings will be of importance when looking at healthcare programs aimed to cut high rates of C-sections which are medically unexplained, particularly during pandemics. Considering the increasing trend of C-section rates in Iran, it seems that new policies to reduce C- sections should consider de-medicalization of birth by strengthening the home birth system.C-section was associated with adverse maternal and neonatal outcomes. Thus, preventing the overuse of C-section especially during pandemic becomes an urgent need for maternal and neonatal health in Iran. Providing individualized support for pregnant women on the most appropriate mode of delivery can reduce the rate of unnecessary C-sections during pandemic. Favoring normal delivery in COVID-19 infected women is paramount, since it reduces the risk of clinical deterioration, and neonatal morbidities related to iatrogenic preterm births , and can


MR-Class is a deep learning-based MR image classification tool for brain images that facilitates and speeds up the initialization of big data MR-based studies by providing fast, robust and quality-assured imaging sequence classifications. Our studies observed up to 10% misclassification rates due to corrupt and misleading DICOM metadata. This highlights the need for a tool such as MR-Class to help with data curation. MR-Class can be integrated into workflows for DICOM inconsistency checks and flagging or completing missing DICOM metadata and thus contribute to the faster deployment of clinical artificial intelligence applications.Background: MR image classification in datasets collected from multiple sources is complicated by inconsistent and missing DICOM metadata. Therefore, we aimed to establish a method for the efficient automatic classification of MR brain sequences. Methods: Deep convolutional neural networks (DCNN) were trained as one-vs-all classifiers to differentiate between six classes: T1 weighted (w), contrast-enhanced T1w, T2w, T2w-FLAIR, ADC, and SWI. Each classifier yields a probability, allowing threshold-based and relative probability assignment while excluding images with low probability . Data from three high-grade glioma (HGG) cohorts was assessed; C1  was used for training, while C2  and C3  were for testing. Two raters manually checked images through an interactive labeling tool. Finally, MR-Class’ added value was evaluated via radiomics model performance for progression-free survival (PFS) prediction in C2, utilizing the concordance index (C-I). Results: Approximately 10% of annotation errors were observed in each cohort between the DICOM series descriptions and the derived labels. MR-Class accuracy was 96.7%  for C2 and 94.4%  for C3. A total of 620 images were misclassified; manual assessment of those frequently showed motion artifacts or alterations of anatomy by large tumors. Implementation of MR-Class increased the PFS model C-I by 14.6% on average, compared to a model trained without MR-Class. Conclusions: We provide a DCNN-based method for the sequence classification of brain MR images and demonstrate its usability in two independent HGG datasets. Magnetic resonance imaging (MRI) has become a crucial imaging modality in the detection and staging of various types of cancer, including brain tumors . With itGueld et al. found that relying on image metadata  to classify medical images can often lead to unreliable results . This isCompared to text-based image classification, content-based image classification (CBIC) is independent of inconsistencies between different image sources, is unaffected by human error, and is less labor-intensive . CBIC meThis work addresses the open-set recognition problem by training a DCNN-based MR image classifier using a one-vs-all approach. Following a comparison study of published DCNNs for medical image classification to determine the chosen DCNN model, one-vs-all binary class-specific DCNN classifiers were trained to recognize a particular MR image, thus forming MR-Class.This study included three datasets: The training/validation cohort (C1) consisted of 320 primary/recurrent high-grade glioma (HGG) patients with a median of 9 image acquisition time points, resulting in 20,101 MR images acquired between 2006 and 2018. The dataset was collected retrospectively from 23 scanners at the Heidelberg University Hospital (UKHD). The first testing cohort (C2) consisted of 197 HGG patients, with a median of 7 time points, resulting in 11,333 images acquired between 2009 and 2017. The dataset was collected retrospectively from 15 different scanners at the UKHD. A public data cohort (C3) was also utilized for the second testing of MR-Class. The data cohort was retrieved from the Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) data collection [Multiparametric MRIs (mpMRI) were collected from multiple scanners in all three datasets, resulting in heterogeneous modalities and MR sequence protocols . Both coIn the context of medical image retrieval and classification using DCNNs, three different DCNNs are present, i.e., ResNet-18 , Φ-Net , and DeeBrief descriptions of the exemplary models behind Φ-Net and DeepDicomSort are given. Visual Geometry Group (VGG) was introduced in 2014 by Simonyan and Zisserman in a paper titled “Very Deep Convolutional Networks for Large-Scale Image Recognition” . The VGG2, and volumes were interpolated to a 2 mm slice thickness. Images were then cropped around the brain into a digital grid of 224 × 224 × 224. Padding was performed when the image shape was smaller than the target grid. Lastly, a z-score normalization of the brain voxels was applied to bring all MR images to the same intensity scale. The formula of the Z-score normalization is as follows:x is the voxel intensity, μ is the mean of the intensity distribution, and σ is the standard deviation.Before training, different preprocessing steps were implemented. The preprocessing pipelines provided by the authors’ GitHub pages were used for the DCNNs trained with Φ-Net and DeepDicomSort. As for the 2D and 3D ResNet-18 DCNNs, magnetic field inhomogeneities of the T1w images were first corrected using the N4ITK algorithm . After rThe 2D and 3D ResNet-18 DCNNs were trained using the deep learning Python library PyTorch (1.7.1) . A stochMR-Class comprises multiple one-vs-all binary classifiers instead of a single multi-class classifier, as used in the comparison study. The rationale behind training multiple one-vs-all DCNNs is the open-set recognition problem and the difficulty of training a DCNN image classifier for every possible MR image. The architecture used for MR-Class was based on the DCNN that achieved the highest accuracy in the comparison study. The training was performed twice using scans from C1. The first training included all MR images available in the dataset, while the second was performed using only the image volumes of the six considered classes (the same images used in the comparison study during training). The latter was conducted to enable a fair comparison of the performance of the one-vs-all dual-class classifiers (MR-Class) against a multi-class DCNN classifier, both trained on the same number of images. For each binary classifier, the classes were defined as follows: class 1 included all images corresponding to the targeted class, while class 0 contained all remaining images in the dataset. A stratified dataset split (by class) of 80% for training and 20% for validation was used , it is deemed unclassifiable. For the 2D DCNNs, an MR scan is classified as a class based on the majority vote of 10 inferred slices extracted from around the middle slice of the corresponding MR acquisition plane. The classifications were compared to the ground truth labels, and accuracy was calculated as the number of correct predictions divided by the total number of images. A 95% confidence interval (CI) was determined using the Wilson interval method . Classifp < 0.05), a random forest (RF)-based method, and lasso regression, were applied separately on 1000 random subsamples of the text-based curated and MR-Class-curated T1wce datasets (10% left out) to identify features correlated to PFS. Significant features identified at least 950 times were selected, and survival analyses were conducted using CPH. Model performances were finally evaluated based on the resampled concordance index (C-I).To demonstrate the applicability of MR-Class in MR-based radiomics applications, Cox proportional hazard models (CPHs) were trained with the T1wce MR sequences of cohort C2 to predict the patients’ progression-free survival (PFS) after performing a text-based curation using the DICOM SDs and a content-based curation using MR-Class . PFS wasBetween all three datasets, 2704 different DICOM SDs were found  and 8–10 h for the 2D DCNN (DeepDicomSort and 2D ResNet-18) on an Intel Xeon processor with 8 cores and 32 Gb of RAM and a graphics card NVIDIA GeForce GTX 1060 (6 Gb). The average inference time was 0.15 s for a single 2D slice and 4.92 s for a 3D image. Thus, the DCNN one-vs-all architecture implemented in MR-Class was that of the 2D ResNet-18  to 99.6% . T1w-vs-T1wce and T1w-vs-all had the lowest sensitivity at 91.9% and 96.6%, respectively, while all other DCNNs had high sensitivity (>99%) , misclassified diffusion-weighted imaging (DWI) as T2w, and DICOM corrupted scans  when the ventricle architecture was altered, such as in cases where it was displaced by large tumors. This misclassification was investigated in detail by using 122 randomly selected correctly labeled images as a reference group. The ground truth volumes (GTVs) and brain were manually segmented, and the Euclidean distance between the CoM of the brain and the CoM of the tumor volume was calculated. A t-test was then performed between the reference and misclassified CoM distributions, which returned a p-value of 0.04. The median distance between CoMs was 46.15 voxels for the correctly labeled images and 66.31 for the misclassified images, indicating a statistical difference between the two groups. In other words, the further the GTV was from the ventricles, the less likely the image was to be misclassified. The frequencies of misclassification categories are presented in Upon manual evaluation, it was discovered that MR-Class frequently misclassified images , followed by a binary classifier for T1w images, to determine whether a contrast agent was administrated. This design enables MR-Class to handle unknown classes since each DCNN only classifies an image if it belongs to its respective class, and thus an image not labeled by any of the DCNNs is rendered as unknown. In order to compare the effectiveness of the multiple one-vs-all binary classifier approach with the basic multi-class classification method, we conducted a multi-class vs multiple dual-class classification experiment. The results showed that both methods achieved a similar classification accuracy for MR brain image classification, with the multi-class method achieving a 98.6% accuracy and the multiple one-vs-all method achieving a 98.1% accuracy. However, the latter approach has an advantage in that it can handle the open-set recognition problem often encountered when dealing with data from clinical cohorts, which can ultimately help reduce MRI study design times.MR image DICOM series description (SD) entries usually follow the MR sequence protocol applied. However, they are MR model specific and are sometimes edited by clinical staff. We observed around 10% discrepancies in each cohort when the SD was compared to the manually derived labels. Typical SDs that do not allow for clear MR scan classifications are SDs with only the sequence name, e.g., spin echo (SE), or the scan direction, e.g., axial, which can stand for any MR sequence. Typographical errors and empty SD attributes were also observed.Overall, high accuracies were obtained for all DCNNs in the comparison study. In conjunction with the high performance achieved in the literature on medical image classification ,14,16,17All six one-vs-all classifiers had high validation accuracies, with the lowest being 97.7% for the T1w-vs-T1wce. After inferring back the training cohort C1 to MR-Class, it was observed that 519 images could not be learned, out of which 336 belonged to class “other”, representing 3.8% of the other images used for training. This low error percentage demonstrates that MR-Class can learn to handle different sequences indirectly.The testing of MR-Class against C2 and C3 yielded an average accuracy of 96.1%, where 620 images (4.2%) were classified incorrectly. Overall, T2w-vs-all had the worst performance, with a specificity of 93.5% and 91.3% in C2 and C3. This is mostly due to the presence of diffusion-weighted imaging (DWI) sequences (frequently encountered in the datasets), which are inherently a series of T2w sequences. Similarly, C3 included T1w-FLAIR images falsely misclassified as T1w or T2w-FLAIR. Thus, different sequences with similar content are prone to misclassification by MR-Class. A solution could be to train a subsequent classifier to distinguish between similar sequences, as performed for the T1wce images. The majority of misclassified images had severe blurring or other MR artifacts. A higher prevalence of misclassifications was observed in C3 compared to C2, and many of these misclassifications were false negatives, resulting in images being labeled as unclassifiable by MR-Class. This could be beneficial for radiomics models as any corrupted images would be automatically disregarded, and all images labeled as a specific class would have analogous content. Another subset of misclassified images showed tumor volumes overlapping with the ventricles, and statistical analysis confirmed that altered anatomy  could be a possible reason for misclassification. However, further analysis is needed to assess the impact of surgery on alterations in overall anatomy, such as biopsy, partial resection, total resection, as well as the effect of treatments such as chemotherapy and radiotherapy on tumor patterns and contrast enhancement.To improve the accuracy of MR-Class and reduce misclassifications, additional data including more diverse MR images should be considered. Additionally, for DWI images misclassified as T2w, a possible solution would be to train a subsequent classifier to distinguish between different MR image protocols, as was done for T1wce images. Another approach to reducing misclassification is to design a workflow that incorporates both text-based and content-based classification (MR-Class). In cases of mismatch between the two methods, manual intervention can be introduced to classify the image correctly. Misclassifications can be corrected through manual label adjustments, and upon the user’s acceptance, these images can be used to retrain the models using a transfer learning approach to improve MR-Class accuracy.An essential step in building a radiomics application is to verify the input data labels before training the machine learning model, as inconsistent data can lead to the model drastically failing . HoweverMR-Class can facilitate the preparation of longitudinal studies for RT treatment assessment as MR data from the three cohorts include scans taken before, after, and throughout the delivery of the RT fractions, which resulted in different tumor volume masses between the different scans, as well as apparent radiation scaring in some of the MR images. Furthermore, the data cohort includes images taken directly after the surgical resection of the tumor, resulting in visible surgical holes and void tumor beds.The 2D DCNNs in this study outperformed their 3D counterparts in classifying MR brain images. This was mostly due to the multiple conventional 2D multislice MR scans acquired in the axial, sagittal, or coronal plane in the three cohorts. However, the classification of MR sequences of a different entity, e.g., abdominal and pelvic MRI, might be more challenging and demand the intrinsic power of 3D DCNN. Due to the frequent presence of 2D images in MR datasets, the reconstruction of these low-resolution 2D slices to a high-resolution 3D MR might be a necessary preprocessing step before training. Nevertheless, the one-vs-all classification pipeline implemented in this study on brain MR images can be used for different anatomy sites and other medical image classification problems, for example, the classification of different body parts and organs.MR-Class is a helpful tool for automating the classification of MR images, thus eliminating the need for manual sorting and saving time for researchers. The tool is particularly useful for studies involving large amounts of data and different naming schemes, as it classifies images based on their content rather than metadata, and can automatically disregard corrupted images. Future work includes expanding the tool to include additional modalities and sequences for different anatomical sites.


Conclusions: After the second year post-LTx, the skeletal complications become less frequent and have similar incidence in patients with CF and nCF.Background: During the first two years after lung transplantation (LTx), the incidence of fragility fractures (FX) is estimated to be 15–50% and it is lower in patients with cystic fibrosis (CF) as compared with other end-stage lung diseases (nCF). The aim of our study is to compare the skeletal outcomes, after the first 2 years post-LTx, in long-term survivors with CF and nCF. Materials and Methods: We evaluated the FX rate, the changes in bone mineral density (BMD) and trabecular bone score (TBS) in 68 patients (38 CF and 30 nCF) who underwent LTx in our center and with a follow-up after LTx longer than 5 years (7.3 ± 2.0 years). Results: After the second year post-LTx: (i) the FX rate was lower than during the first two years post-LTx (4.4 vs. 20.6%,  End-stage respiratory failure is associated with a deterioration in bone health and lung transplant (LTx) candidates often present osteoporosis and fragility fractures (FX), with an estimated prevalence reaching 60% and 50%, respectively ,10,11,12The initial worsening in bone status after LTx is partly explained by immobilization and use of immunosuppressive therapies , even though, also, the LTx per se seems to play a role ,17. AlthThe few studies in the literature on long-term skeletal outcomes in LTx recipients suggest that, over time, BMD becomes stable and the FX rate decreases ,21,22 buThe aim of our study is to compare the skeletal outcomes after the first 2 years post-LTx between long-term LTX survivors with CF and those with nCF.In this retrospective longitudinal study, we included all consecutive patients aged ≥20 years with end-stage lung disease referred as LTx candidates to the Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico  from January 2009 to December 2016 who eventually underwent LTX and survived >5 years thereafter. The exclusion criteria were other organ transplantation before LTx or within 5 years after and incomplete bone workup at enrollment.During the study period, 136 patients underwent LTx. Among these patients, 16 patients did not complete the bone workup at enrollment, 8 underwent other solid organ transplant, 43 patients died within 5 years after LTx and 1 patient was lost at follow-up. Among the remaining 68 patients included in this study, 38 and 30 were CF and nCF, respectively. In the nCF group 5, 12, 5 and 8 patients were affected with chronic-obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), connective tissue disease associated with interstitial lung disease (CTD-ILD) and rare lung diseases (RLD), respectively.The steroid regimen used at our center is methylprednisolone intraoperatively 500–1000 mg (intravenous—IV—weight-adjusted dose) at time of reperfusion, 0.5 mg/Kg IV twice per day for the first 3 days postoperatively, then oral prednisone tapered over 18–24 months post-transplant .https://www.aifa.gov.it/nota-79, accessed on 6 February 2023). From the third year post-LTX, the therapy discharge was tailored according to the fracture risk, which was reassessed at each medical check-up.A bone-active therapy was proposed to all patients during the workup before being considered admissible on the transplant list regardless of BMD and prevalent FX . The typA cholecalciferol supplementation per os was introduced in all patients. The standard maintenance cholecalciferol dose was 400 or 800 IU daily plus 100,000 IU bolus per month, in addition to specific multivitamin supplementation in CF group . CalciumWe collected information about body mass index (BMI), daily calcium intake, current and past exposure to GC, hypogonadism, previous and ongoing bone-active therapies and prevalent FX during the workup before the patient was considered admissible on the transplant list. The calcium intake was assessed using a validated 7-day food frequency questionnaire . A fractThe 25-hydroxyvitamin-D (25OHD) and testosterone levels were measured by chemiluminescent  and electrochemiluminescent immunoassay , respectively, during the workup before the patient was considered admissible on the transplant list and at each bone follow-up (approximately every 2 years). Serum samples were collected and stored at −20 °C until assayed, regardless of the season. Hypovitaminosis-D was defined as 25OHD below the reference range  and severe deficiency as 25OHD below 25 nmol/L (10 ng/mL). Untreated hypogonadism was defined as the association of low testosterone levels and signs and symptoms of hypogonadism in males and secondary amenorrhea (lasting longer than 3-month) in females, without ongoing hormonal replacement therapy.We also collected dual X-ray absorptiometry (DXA) and spine radiograph data during the workup before the patient was considered admissible on the transplant list 2 years after LTx and at last available follow-up. The DXA  scan was carried out to measure BMD at lumbar spine , total hip , femoral neck  and TBS. The BMD data were expressed as T-score (BMD difference in standard deviation (SD) in comparison with healthy 30-year-old individuals of the same gender, as provided by the manufacturer) and Z-score . The TBS values were expressed as Z-score based on normal reference ranges derived from the Italian population . FracturThe DXA data were available from all patients at baseline and 24 months after LTx and from 55 patients at last follow-up. TBS data were available from 58 patients at baseline, from 46 patients at 24 months and from 49 patients at last follow-up. Spine radiograph data were available from all patients at each timepoint.t-test or Mann–Whitney U-test, respectively, as appropriate. Categorical variables were compared by χ2 test or Fisher exact test, as appropriate. ANOVA for repeated measures was used to compare data between baseline and follow-up. The fracture-free survival probability per year was assessed by the Kaplan–Meier method.Statistical analysis was performed by SPSS version-24.0 statistical package . The normality distribution was checked by the Kolmogorov–Smirnov test. Variables were expressed as mean ± standard deviation if normally distributed and as median (interquartile range) if not normally distributed; the comparison was performed using one-way Student p values < 0.05 were considered significant.The clinical and biochemical characteristics of patients at baseline are reported in The clinical characteristics of the patients at last available follow-up are reported in p = 0.002) (p = 0.045) and in the nCF group  and remained stable in CF patients . As compared with CF patients, patients with nCF had significantly higher FX rate during the first year after LTx but not during the subsequent follow-up period  occurring in 13 patients (4 in CF and 13 in nCF patients) with an incidence of 10.5% in CF group and 43.3% in nCF group (= 0.002) . After tp period .p = 0.0006), whereas the rate of nonvertebral FX was not significantly different between the first 2 years of follow-up and the subsequent period .Only three patients (4.4%) had incident FX after the second year post-LTx and all fractures were not at spine and fractured patients were as follows: a 28-year-old CF female with hip FX five years after LTx, a 58-year-old CF female with wrist FX six years after LTx and a 65-year-old nCF male with wrist FX five years after LTx. The 28-year-old CF patient and the nCF 65-year-old male patient were still taking pharmacological treatment because of persistent high FX risk due to organ rejection, whereas the 58-year-old CF patient had never taken a bone-active drug during the whole follow-up. The vertebral FX rate markedly decreased from the first two years after LTx to the subsequent period of follow-up . Overall, the HR for FX was 6.9 for nCF patients as compared with CF ones. Stratifying the analysis in early (first 2 years post-LTx) and late (from the third year post-LTx) time points, we calculated that the HR passed from 5.5 p = 0.012 to 0 p = 1, respectively.The Fx-free survival probability after LTx in patients with cystic fibrosis and other end-stage lung disease is represented in p = 0.450).The BMD and TBS variations after LTx are reported in p = 0.027, 0.6 ± 1.4, p = 0.005, −0.7 ± 0.9, p = 0.026, 1.6 ± 0.9 p = 0.016, respectively). Nevertheless, after the second year post-LTx, BMD and TBS did not change significantly between patients taking bone-active therapy and untreated patients and there was no difference in the FX rate between treated patients and untreated patients in this time frame.A total of 17 patients (25%) were taking bone-active therapy after the second year post-LTx, of which 11 (20.4%) were also treated before and 6 (8.8%) introduced a bone-active drug only later. The compliance to bone-active therapy was assessed at each time point and was >85% in all patients. As expected, since the therapy discharge was tailored according to the fracture risk, the patients taking bone-active therapy after the second year post-LTx had a more severe skeletal impairment. They had higher FX rate during the first two years (33.3%) and SDI (4 ± 6), lower LS T-score (−1.6 ± 0.9) and FN T-score (−2.2 ± 0.8) at the second year post-LTx as compared with patients who were not taking bone-active therapy , TBS may explain the discrepancy between the BMD behavior and the FX risk . Indeed,The change in the site of FX over time  can be explained by the fact that vertebrae are rich in trabecular bone, which is very sensitive to GC use, even in the short term . Indeed,This study has some strengths and some limitations. The strength of our study is firstly related to the fact that the baseline assessment was systematically performed for all patients very close to the LTx and the periodical re-evaluation always included the vertebral morphometry. Secondly, information on bone quality, even though by means of an indirect marker such as TBS, has been obtained for the first time in these subjects consenting to show a different behavior of LTx-related bone damage between patients with nCF and those with CF. Finally, this is the first study showing the long-term skeletal outcomes in LTx patients being evaluated and managed appropriately from the moment of LTx and periodically re-evaluated thereafter.The limitations of the present study are related firstly to the relatively low sample size and secondly to the fact that data were not available for all patients at each time point due to the retrospective nature of this study. Finally, information on physical activity and on the bone turnover parameters that could have been more informative is lacking.In conclusion, we already knew that LTx recipients were at high risk of FX, especially at vertebral sites during the first two years after LTx, suggesting the need for taking charge of these patients at the time of LTx listing. Importantly, these new data suggest that, although patients with non-CF lung disease are more often affected by FX during the first two years post-LTx as compared with CF ones, the same cannot be said afterwards. Finally, as for other forms of secondary osteoporosis, TBS could be a sensitive tool to monitor and estimate the risk of FX in transplanted patients .